Biometric personal identification system based on iris analysis
DCFirst Claim
1. A method for uniquely identifying a particular human being by biometric analysis of the iris of the eye, comprising the following steps:
- acquiring an image of an eye of the human to be identified;
isolating and defining the iris of the eye within the image, wherein said isolating and defining step includes the steps of;
defining a circular pupillary boundary between the iris and pupil portions of the image;
defining another circular boundary between the iris and sclera portions of the image, using arcs that are not necessarily concentric with the pupillary boundary;
establishing a polar coordinate system on the isolated iris image, the origin of the coordinate system being the center of the circular pupillary boundary, wherein the radial coordinate is measured as a percentage of the distance between the said circular pupillary boundary and said circular boundary between the iris and sclera; and
defining a plurality of annular analysis bands within the iris image;
analyzing the iris to generate a presenting iris code;
comparing said presenting code with a previously generated reference iris code to generate a measure of similarity between said presenting iris code and said reference code;
converting said similarity measure into a decision that said iris codes either do or do not arise from the same iris; and
calculating a confidence level for the decision.
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Abstract
A system for rapid and automatic identification of persons, with very high reliability and confidence levels. The iris of the eye is used an optical fingerprint, having a highly detailed pattern that is unique for each individual and stable over many years. Image analysis algorithms find the iris in a live video image of a person'"'"'s face, and encode its texture into a compact signature, or "iris code." Iris texture is extracted from the image at multiple scales of analysis by a self-similar set of quadrature (2-D Gabor) bandpass filters defined in a dimensionless polar coordinate system. The sign of the projection of many different parts of the iris onto these multi-scale quadrature filters, determines each bit in an abstract (256-byte) iris code. The degrees-of-freedom in this code are based on the principle forms of variation in a population of irises studied. Because of the universal mathematical format and constant length of the iris codes, comparisons between them are readily implemented by the Exclusive-OR (XOR) logical operation. Pattern recognition is achieved by combining special signal processing methods with statistical decision theory, leading to a statistical test of independence based on a similarity metric (the Hamming distance) that is computed from the XOR of any two iris codes. This measure positively establishes, confirms, or disconfirms, the identity of any individual. It also generates an objective confidence level associated with any such identification decision.
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Citations
21 Claims
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1. A method for uniquely identifying a particular human being by biometric analysis of the iris of the eye, comprising the following steps:
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acquiring an image of an eye of the human to be identified; isolating and defining the iris of the eye within the image, wherein said isolating and defining step includes the steps of; defining a circular pupillary boundary between the iris and pupil portions of the image; defining another circular boundary between the iris and sclera portions of the image, using arcs that are not necessarily concentric with the pupillary boundary; establishing a polar coordinate system on the isolated iris image, the origin of the coordinate system being the center of the circular pupillary boundary, wherein the radial coordinate is measured as a percentage of the distance between the said circular pupillary boundary and said circular boundary between the iris and sclera; and defining a plurality of annular analysis bands within the iris image; analyzing the iris to generate a presenting iris code; comparing said presenting code with a previously generated reference iris code to generate a measure of similarity between said presenting iris code and said reference code; converting said similarity measure into a decision that said iris codes either do or do not arise from the same iris; and calculating a confidence level for the decision. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21)
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Specification